It made me 2x slower, because with Claude's hallucinations I waste more time chasing dead ends than I gain from it in productivity.
Ask HN: By what percentage has AI changed your output as a software engineer?
11–20 of 96 posts
Re: Ask HN: By what percentage has AI changed your output as a software engineer?
#12For me it feels like roughly a 10–20x change, but mostly because I restructured how I work rather than just adding an “AI helper” on top. In the last year I’ve shipped a couple of small OSS tools that I almost certainly would not have finished without AI‑assisted “vibe coding”. Everything I build now flows through AI, but in a slightly different way than just chatting with an LLM. I rarely use standalone ChatGPT/Gemi…
If you were 20x faster you'd have done an entire career's worth of progress this year.
Have you? Are you making tons of money? Have you achieved 20x the amount than you have all previous years?
Take a step back and realize what you're claiming here.
Re: Ask HN: By what percentage has AI changed your output as a software engineer?
#13It made me 2x slower, because with Claude's hallucinations I waste more time chasing dead ends than I gain from it in productivity.
[flagged]
Re: Ask HN: By what percentage has AI changed your output as a software engineer?
#140% productivity improvement.
Rephrasing the question: By what percentage has AI changed your input quality?
Answer would be around -50%. This is attributed mostly to the vast amount of search results that are AI generated and provide very low density information and miss conveying actual key learning points. This means you have to scan through 100% more text to finally get the information you need to solve the issue. I think this is a low estimate actually.
Re: Ask HN: By what percentage has AI changed your output as a software engineer?
#15I'm learning Python on the job, with decades of experience in other languages. Asking an LLM noob Python questions is probably 5-10x faster than googling around and reading docs or tutorials, and almost 100% accurate. I also ask it about git commands I seldom use (I tend to confuse reset and restore, though not revert for some reason).
Introductory questions about a widely used language with great documentation and tons of tutorials are made for LLMs.
Re: Ask HN: By what percentage has AI changed your output as a software engineer?
#16How would we describe the productivity gains brought on by engaging with tasks we did not have the ability or confidence to prior? The denominator looks like a zero in many places for me.
Re: Ask HN: By what percentage has AI changed your output as a software engineer?
#1710x when working on a code base I'm very familiar with.
Basically, it amounts to being able to give detailed instructions to a junior dev (who can type incredibly fast) and having them carry out your instructions.
If you don't know the code base, and thus can't provide detailed instructions, this junior dev can (using their incredible typing speed) quickly run off the rails. In this case, as you don't know the code base, you wouldn't know it's off the rails. So you're S.O.L.
Re: Ask HN: By what percentage has AI changed your output as a software engineer?
#18For me it feels like roughly a 10–20x change, but mostly because I restructured how I work rather than just adding an “AI helper” on top. In the last year I’ve shipped a couple of small OSS tools that I almost certainly would not have finished without AI‑assisted “vibe coding”. Everything I build now flows through AI, but in a slightly different way than just chatting with an LLM. I rarely use standalone ChatGPT/Gemi…
If you were 20x faster you'd have done an entire career's worth of progress this year. Have you? Are you making tons of money? Have you achieved 20x the amount than you have all previous years? Take a step back and realize what you're claiming here.
It could be ie 2x faster with 10x less staff/cost as well, right?
Re: Ask HN: By what percentage has AI changed your output as a software engineer?
#19It really helps where the code I'm writing fits the broad description of boilerplate.
Need to integrate Stripe with the Clerk API in my Astro project? Claude's all over that. 300% faster. I think of it like, if there was a package that did exactly what I wanted, I'd use that package. There just happens not to be; but Claude excels at package-like code.
But as soon as I need to write any unique code – the code that makes my app my app – I find it's perhaps a touch faster in the moment, but the long-term result isn't faster.
Because now I don't understand my code, right? How could I. I didn't write it. So as soon as something goes wrong, or I want to add a feature, either I exacerbate this problem by getting Claude to do it, or I have to finally put in the work that I should have put in the first time.
Or I have to spend about the same amount of time creating a CLAUDE.md that I would have if I'd just figured out the code myself. Except now the thing I learned is how to tell a machine how to do something that I actually enjoy doing myself. So I never learn; on the contrary, I feel dumber. Which seems a bit weird.
And if I choose the lazy option here and keep deferring my knowledge to Claude, now I'm charging customers for a thing that I 'vibe coded'. And frankly if you're doing that I don't know how you sleep at night.
Re: Ask HN: By what percentage has AI changed your output as a software engineer?
#20I'd say on average about 50% faster but it really depends on the task at hand. On problems that can be isolated pretty well like a new feature that is relatively isolated (for example building a file export in a specific format) it's easily a 10x speed up.
One thing that generally gets less talked about is exploration of the solution space during manual implementation. I work in a very small company and we build a custom ERP solution. Our development process is very stripped down (a good thing IMO). Often times when we get new requirements we brain storm and make a rough design. Then I try implement it and during that phase new questions and edge cases arise, and at any time this happens we adjust the design. In my opinion this is very productive as the details of the design are worked out when I already know the related code very well as I already got down to implementing. This leads to a better fitting design and implementation. Unfortunately this exploration workflow is incompatible with llms if you use them to do the implementation for you. Which means that you have put more effort in the design up front. From my experience that means the gain in speed in such task is nullified and also results in code that fits worse into the rest of the codebase.